I hail from a small city in central India (also called "Heart of India"). In 2016, I came to the United States for my Masters at NYU and ended up doing my PhD at UCSD, thanks to my MS thesis advisor Prof. Shivendra Panwar, and my PhD guide Prof. Dinesh Bharadia. I miss the subway train and Indian food of New York, but, I like the weather and beaches of San Diego. During my free times, I enjoy sketching, painting, and writing personal blogs.
Enabling low latency and reliable VR over mmWave networks
We are developing a new optimization framework to transfer VR video over either WiFi or WiGig interface with high reliability and low latency.
We analyze the impact of blockage by static buildings, mobile blockers as well as self-blockage by the user's body. Our results indicate that the minimum density of BS required to satisfy the Quality of Service (QoS) requirements of Ultra Reliable Low Latency Communication (URLLC) applications is mainly driven by reliability and latency constraints, rather than coverage or capacity requirements.
Collaborators: Rajeev Kumar, NYU
Code Paper Masters Thesis
We implemented 7 queue management schemes including ARED, CoDel, PIE, and SFQ on GENI testbed and analyzed their performances in residential settings.
CodePublished : "Study of use of Water based Solvent in Ink Homogenization."
International Journal of Engineering Research & Technology. Vol. 3 - Issue 7, July 2014.
Studied the colour homogenization and its production with the use of water based solvent, through experiments. Fabricated a device which can sense and produce same colour using different proportion of CMYK ink and solvent.
Made a platform which is balanced horizontally with the help of three motors, irrespective of the movement of the base at the bottom. Used an accelerometer and gyroscope based IMU to get the feedback of the tilt of platform and processed the signal in an Arduino Mega. Applied PID control and kalman filter algorithm to stabilise the platform obtained by precise movement of servos in real time.
Mentor: Ozge Kaya
Developed beam training algorithm for initial access in mmWave Network. It allows the users to connect to the mmWave access point faster than the traditional exhaustive search scheme using directional beams. The algorithm is robust to channel variations, blockages, and user's mobility.
Mentor: Dr. Jianping Pan, Dept. of Computer Science
Studied state-of-the-art Rendezvous algorithms for Cognitive Radio Networks and obtained channel availability probability for cognitive users based on primary users location in a cellular model, which is used to evaluate the rendezvous performance in the practical conditions.
Step-1: Use Git-Bash in Windows (or terminal in Linux) and login to hpc as follow...
It's time to thank all the professors at IITK who guided us through the 4 years of the best period of our life...